Performance comparison of structural stormwater best management practices.

This paper describes a method for comparing the pollutant removal of a number of structural stormwater treatment devices, commonly referred to as best management practices (BMPs). Historically, the pollutant removal ability of a BMP has been expressed as a percent reduction in concentration or load. Unfortunately, the calculated percent reduction in pollutant concentration is strongly affected by the influent concentration, with the calculated reduction generally being much lower when the event mean concentrations (EMCs) in the untreated runoff from the test watershed are low. The objective of the proposed methodology is to eliminate this problem by predicting BMP performance for an arbitrary influent concentration, so that BMPs evaluated in different watersheds can be compared as if the influent quality at all sites were the same. This method allows BMPs to be compared based on the quality of effluent produced and the mass reduction. The proposed method uses linear regression as the primary tool to compute the expected effluent concentration from a BMP, given a specific influent concentration of interest and was developed using data collected in the California Department of Transportation BMP Retrofit Pilot Program. This technique reveals that for media filters, the concentration of sediment and other particle-associated pollutants in treated runoff is generally unrelated to influent quality and is relatively constant. Wet basins with large permanent pool volumes also have effluent concentrations that are constant for most constituents and unrelated to influent concentrations. In these situations, the "percent reduction" in a pollutant EMC is not an inherent characteristic of the BMP, but a function of the influent EMC, because the quality of effluent produced is constant. Predicting the effluent quality of several types of conventional BMPs based on a common influent concentration allows an objective comparison of their performance and the selection of a BMP that addresses specific constituents of concern.